818 resultados para Linear matrix inequalities (LMI) techniques
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Background: Preventing ridge collapse with the extraction of maxillary anterior teeth is vital to an esthetic restorative result. Several regenerative techniques are available and are used for socket preservation. The aim of this study is to analyze by clinical parameters the use of acellular dermal matrix (ADM) and anorganic bovine bone matrix (ABM) with synthetic cell-binding peptide P-15 to preserve alveolar bone after tooth extraction. Methods: Eighteen patients in need of extraction of maxillary anterior teeth were selected and randomly assigned to the test group (ADM plus ABM/P-15) or the control group (ADM only). Clinical measurements were recorded initially and at 6 months after ridge-preservation procedures. Results: In the clinical measurements (external vertical palatal measurement [EVPM], external vertical buccal measurement [EVBM], and alveolar horizontal measurement [AHM]) the statistical analysis showed no difference between test and control groups initially and at 6 months. The intragroup analysis, after 6 months, showed a statistically significant reduction in the measurements for both groups. In the comparison between the two groups, the differences in the test group were as follows: EVPM = 0.83 +/- 1.53 mm; EVBM = 1.20 +/- 2.02 mm; and AHM = 2.53 +/- 1.81 mm. The differences in the control group were as follows: EVPM = 0.87 +/- 1.13 mm; EVBM = 1.50 +/- 1.15 mm; and AHM = 3.40 +/- 1.39 mm. The differences in EVPM and EVBM were not statistically significant; however, in horizontal measurement (AHM), there was a statistically significant difference (P<0.05). Conclusion: The results of this study show that ADM used as membrane associated with ABM/P-15 can be used to reduce buccal-palatal dimensions compared to ADM alone for preservation of the alveolar ridge after extraction of anterior maxillary teeth. J Periodontol 2011;82:72-79.
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During embryo implantation, invasive trophoblast cells mediate embryo invasion into the decidualized stroma, forming a rich network of lacunae that connect the embryonic tissues to the maternal blood vessels. Placentation is probably guided by the composition and organization of the endometrial extracellular matrix. Certain pathological conditions that occur during pregnancy, including diabetes, have been linked to abnormal placental morphology and consequent fetal morbidity. We used immunoperoxidase techniques to identify members of the collagen, proteoglycan and glycoprotein families in the various compartments of the rat placenta and to determine whether experimentally induced diabetes affects placental morphology and alters the distribution of these molecules during pregnancy. Single injections of alloxan (40 mg kg(-1) i.v.) were used to induce diabetes on day 2 of pregnancy in Wistar rats. Placentas were collected on days 14, 17, and 20. Type I and III collagen, as well as the proteoglycans decorin and biglycan, were found to be distributed throughout the placentas of control and diabetic rats. In both groups, laminin expression decreased at the end of pregnancy. In contrast, fibronectin was detected in the labyrinth region of diabetic rats at all gestational stages studied, whereas it was detected only at term pregnancy in the placentas of control rats. These results show for the first time that some extracellular matrix molecules are modulated during placental development. However, as diabetic rats presented increased fibronectin deposition exclusively in the labyrinth region, we speculate that diabetes alters the microenvironment at the maternal-fetal interface, leading to developmental abnormalities in the offspring.
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Conventional procedures employed in the modeling of viscoelastic properties of polymer rely on the determination of the polymer`s discrete relaxation spectrum from experimentally obtained data. In the past decades, several analytical regression techniques have been proposed to determine an explicit equation which describes the measured spectra. With a diverse approach, the procedure herein introduced constitutes a simulation-based computational optimization technique based on non-deterministic search method arisen from the field of evolutionary computation. Instead of comparing numerical results, this purpose of this paper is to highlight some Subtle differences between both strategies and focus on what properties of the exploited technique emerge as new possibilities for the field, In oder to illustrate this, essayed cases show how the employed technique can outperform conventional approaches in terms of fitting quality. Moreover, in some instances, it produces equivalent results With much fewer fitting parameters, which is convenient for computational simulation applications. I-lie problem formulation and the rationale of the highlighted method are herein discussed and constitute the main intended contribution. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 113: 122-135, 2009
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We consider the three-particle scattering S-matrix for the Landau-Lifshitz model by directly computing the set of the Feynman diagrams up to the second order. We show, following the analogous computations for the non-linear Schrdinger model [1, 2], that the three-particle S-matrix is factorizable in the first non-trivial order.
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Using the first-principles real-space linear muffin-tin orbital method within the atomic sphere approximation (RS-LMTO-ASA) we study hyperfine and local magnetic properties of substituted pure Fe and Fe-Cu clusters in an fcc Cu matrix. Spin and orbital contributions to magnetic moments, hyperfine fields and the Mossbauer isomer shifts at the Fe sites in Fe precipitates and Fe-Cu alloy clusters of sizes up to 60 Fe atoms embedded in the Cu matrix are calculated and the influence of the local environment on these properties is discussed.
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The magnetic linear dichroism (MLD) at band-edge photon energies in the Voigt geometry was calculated for EuTe. At the spin-flop transition, MLD shows a step-like increase. Above the spin-flop transition MLD slowly decreases and becomes zero when the averaged electronic charge becomes symmetric relative to the axis of light propagation. Further increase of the magnetic field causes ferromagnetic alignment of the spins along the magnetic field direction, and MLD is recovered but with an opposite sign, and reaches maximum absolute values. These results are explained by the rearrangement of the Eu(2+) spin distribution in the crystal lattice as a function of magnetic field, due to the Zeeman interaction, demonstrating that MLD can be a sensitive probe of the spin order in EuTe, and provides information that is not accessible from other magneto-optical techniques, such as magnetic circular dichroism measurement studies.
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Pb(2)CrO(5) nanoparticles were embedded in an amorphous SiO(2) matrix by the sol-gel process. The pH and heat treatment effects were evaluated in terms of structural, microstructural and optical properties from Pb(2)CrO(5)/SiO(2) compounds. X-ray diffraction (XRD), high resolution transmission electron microscopy (HR-TEM), energy dispersive spectroscopy (EDS), and diffuse reflectance techniques were employed. Kubelka-Munk theory was used to calculate diffuse reflectance spectra that were compared to the experimental results. Finally, colorimetric coordinates of the Pb(2)CrO(5)/SiO(2) compounds were shown and discussed. In general, an acid pH initially dissolves Pb(2)CrO(5) nanoparticles and following heat treatment at 600 A degrees C crystallized into PbCrO(4) composition with grain size around 6 nm in SiO(2) matrix. No Pb(2)CrO(5) solubilization was observed for basic pH. These nanoparticles were incorporated in silica matrix showing a variety of color ranging from yellow to orange.
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Two Augmented Lagrangian algorithms for solving KKT systems are introduced. The algorithms differ in the way in which penalty parameters are updated. Possibly infeasible accumulation points are characterized. It is proved that feasible limit points that satisfy the Constant Positive Linear Dependence constraint qualification are KKT solutions. Boundedness of the penalty parameters is proved under suitable assumptions. Numerical experiments are presented.
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We consider a generalized leverage matrix useful for the identification of influential units and observations in linear mixed models and show how a decomposition of this matrix may be employed to identify high leverage points for both the marginal fitted values and the random effect component of the conditional fitted values. We illustrate the different uses of the two components of the decomposition with a simulated example as well as with a real data set.
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Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit. Often, the number of observations is small, and it is thus important to use inference strategies that incorporate small sample corrections. In this paper, we develop modified versions of the likelihood ratio test for fixed effects inference in mixed linear models. In particular, we derive a Bartlett correction to such a test, and also to a test obtained from a modified profile likelihood function. Our results generalize those in [Zucker, D.M., Lieberman, O., Manor, O., 2000. Improved small sample inference in the mixed linear model: Bartlett correction and adjusted likelihood. Journal of the Royal Statistical Society B, 62,827-838] by allowing the parameter of interest to be vector-valued. Additionally, our Bartlett corrections allow for random effects nonlinear covariance matrix structure. We report simulation results which show that the proposed tests display superior finite sample behavior relative to the standard likelihood ratio test. An application is also presented and discussed. (C) 2008 Elsevier B.V. All rights reserved.
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Modeling of spatial dependence structure, concerning geoestatistics approach, is an indispensable tool for fixing parameters that define this structure, applied on interpolation of values in places that are not sampled, by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations on sampled data. Thus, this trial aimed at using diagnostics techniques of local influence in spatial linear Gaussians models, applied at geoestatistics in order to evaluate sensitivity of maximum likelihood estimators and restrict maximum likelihood to small perturbations in these data. So, studies with simulated and experimental data were performed. Those results, obtained from the study of real data, allowed us to conclude that the presence of atypical values among the sampled data can have a strong influence on thematic maps, changing, therefore, the spatial dependence. The application of diagnostics techniques of local influence should be part of any geoestatistic analysis, ensuring that the information from thematic maps has better quality and can be used with greater security by farmers.
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The Birnbaum-Saunders regression model is commonly used in reliability studies. We derive a simple matrix formula for second-order covariances of maximum-likelihood estimators in this class of models. The formula is quite suitable for computer implementation, since it involves only simple operations on matrices and vectors. Some simulation results show that the second-order covariances can be quite pronounced in small to moderate sample sizes. We also present empirical applications.
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In this paper we show the results of a comparison simulation study for three classification techniques: Multinomial Logistic Regression (MLR), No Metric Discriminant Analysis (NDA) and Linear Discriminant Analysis (LDA). The measure used to compare the performance of the three techniques was the Error Classification Rate (ECR). We found that MLR and LDA techniques have similar performance and that they are better than DNA when the population multivariate distribution is Normal or Logit-Normal. For the case of log-normal and Sinh(-1)-normal multivariate distributions we found that MLR had the better performance.
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In this work, we introduce a necessary sequential Approximate-Karush-Kuhn-Tucker (AKKT) condition for a point to be a solution of a continuous variational inequality, and we prove its relation with the Approximate Gradient Projection condition (AGP) of Garciga-Otero and Svaiter. We also prove that a slight variation of the AKKT condition is sufficient for a convex problem, either for variational inequalities or optimization. Sequential necessary conditions are more suitable to iterative methods than usual punctual conditions relying on constraint qualifications. The AKKT property holds at a solution independently of the fulfillment of a constraint qualification, but when a weak one holds, we can guarantee the validity of the KKT conditions.
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To identify chemical descriptors to distinguish Cuban from non-Cuban rums, analyses of 44 samples of rum from 15 different countries are described. To provide the chemical descriptors, analyses of the the mineral fraction, phenolic compounds, caramel, alcohols, acetic acid, ethyl acetate, ketones, and aldehydes were carried out. The analytical data were treated through the following chemometric methods: principal component analysis (PCA), partial least square-discriminate analysis (PLS-DA), and linear discriminate analysis (LDA). These analyses indicated 23 analytes as relevant chemical descriptors for the separation of rums into two distinct groups. The possibility of clustering the rum samples investigated through PCA analysis led to an accumulative percentage of 70.4% in the first three principal components, and isoamyl alcohol, n-propyl alcohol, copper, iron, 2-furfuraldehyde (furfuraldehyde), phenylmethanal (benzaldehyde), epicatechin, and vanillin were used as chemical descriptors. By applying the PLS-DA technique to the whole set of analytical data, the following analytes have been selected as descriptors: acetone, sec-butyl alcohol, isobutyl alcohol, ethyl acetate, methanol, isoamyl alcohol, magnesium, sodium, lead, iron, manganese, copper, zinc, 4-hydroxy3,5-dimethoxybenzaldehyde (syringaldehyde), methaldehyde (formaldehyde), 5-hydroxymethyl-2furfuraldehyde (5-HMF), acetalclehyde, 2-furfuraldehyde, 2-butenal (crotonaldehyde), n-pentanal (valeraldehyde), iso-pentanal (isovaleraldehyde), benzaldehyde, 2,3-butanodione monoxime, acetylacetone, epicatechin, and vanillin. By applying the LIDA technique, a model was developed, and the following analytes were selected as descriptors: ethyl acetate, sec-butyl alcohol, n-propyl alcohol, n-butyl alcohol, isoamyl alcohol, isobutyl alcohol, caramel, catechin, vanillin, epicatechin, manganese, acetalclehyde, 4-hydroxy-3-methoxybenzoic acid, 2-butenal, 4-hydroxy-3,5-dimethoxybenzoic acid, cyclopentanone, acetone, lead, zinc, calcium, barium, strontium, and sodium. This model allowed the discrimination of Cuban rums from the others with 88.2% accuracy.